How to implement AI strategies
Playtime is over Report
AI offers companies and individual departments enormous potential to significantly optimize business models, investment logic, human capital and central processes and structures. A well-planned AI strategy is essential for maximizing these opportunities. It is the key success factor for ensuring the effective development, implementation, and scaling of AI projects. Our new report is designed to help you with exactly that.
Our experts will show you how to effectively prepare and implement well thought-out and planned AI projects. From setting objectives and selecting the right use cases to an overview of the most important ecosystems: The trial-and-error phase is over - now it's time for putting plans into action!
The four key elements of a successful
AI strategy
Objective
The goals of the AI strategy should be in line with the company's overall strategy. The strategy determines the areas in which AI can create the greatest added value and the commitment required to achieve this.
Use Cases
Once the goals have been defined, the next step is to convert them into AI use cases. The objective is to identify, evaluate and prioritize practicable AI use cases in the defined fields of action. In our report, we show you how this can be achieved in just five steps.
Enabler
To use AI successfully and safely, collaboration with partners is essential. Not everything has to be done internally. To define an AI ecosystem strategy, it is necessary to clarify which partners can assist in specific situations and determine the most effective way to collaborate with them.
Implementation
These areas play a special role in the implementation of the AI strategy: research & exploration, development & validation, and operationalization & operation. An iterative approach enables you to learn from the initial use cases and continuously adapt the strategy.
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